Differential Analysis, RNA-seq data eye regeneration time course

Code for this DE analysis can be found at maple.sgc.loc/home/bp2582/projects/eye-reg_rnaseq/github/SnailEyeReg_RNASeq/code/DEAnalysis.Rmd.

I performed DE analysis using the edgeR package and its pipeline (https://bioconductor.org/packages/release/bioc/html/edgeR.html)

Characteristics of the analysis:

• I computed genewise exact tests and a tagwise dispersion
• As a cutoff I used adj p-val(FDR) >= 1e-5 and logFC >= |2|
• I produced MA and Volcano plots

MA plots

With intact eye as a baseline

Paiwise comparisons

Volcano plots

With intact eye as a baseline

3dpa-intact

6dpa-intact

6dpa-intact

9dpa-intact

12dpa-intact

15dpa-intact

21dpa-intact

28dpa-intact

Paiwise comparisons

3dpa-1dpa

6dpa-3dpa

9dpa-6dpa

12dpa-9dpa

15dpa-12dpa

21dpa-15dpa

28dpa-21dpa

intact-28dpa

Gene lists

Can be found at maple.sgc.loc/home/bp2582/projects/eye-reg_rnaseq/github/SnailEyeReg_RNASeq/data/tables/DEAnalysis/DEGenes/logFC2-cutoff/de/

I noticed that the amount of genes obtained with these cutoffs where low in some of the comparisons, so I decided to plot the amount of DE genes along the different comparisons. Code can be found at maple.sgc.loc/home/bp2582/projects/eye-reg_rnaseq/github/SnailEyeReg_RNASeq/code/PlotDE-ct_logFC2-1e-5.Rmd.

Given there are comparisons with few DEs I will loose the logFC cuttoff so I can use a bigger list to run GO term.